Literature DB >> 31101764

Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in Over 140,000 European Descendants.

Lang Wu1,2, Jifeng Wang1,3, Qiuyin Cai1, Taylor B Cavazos4, Nima C Emami4,5, Jirong Long1, Xiao-Ou Shu1, Yingchang Lu1, Xingyi Guo1, Joshua A Bauer6,7, Bogdan Pasaniuc8, Kathryn L Penney9,10, Matthew L Freedman, Zsofia Kote-Jarai11, John S Witte4,5, Christopher A Haiman12, Rosalind A Eeles11, Wei Zheng13.   

Abstract

Genome-wide association study-identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 × 10-6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 × 10-6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology. SIGNIFICANCE: This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer. ©2019 American Association for Cancer Research.

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Year:  2019        PMID: 31101764      PMCID: PMC6606384          DOI: 10.1158/0008-5472.CAN-18-3536

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  53 in total

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Review 2.  Transcriptional regulatory elements in the human genome.

Authors:  Glenn A Maston; Sara K Evans; Michael R Green
Journal:  Annu Rev Genomics Hum Genet       Date:  2006       Impact factor: 8.929

3.  Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses.

Authors:  Oliver Stegle; Leopold Parts; Matias Piipari; John Winn; Richard Durbin
Journal:  Nat Protoc       Date:  2012-02-16       Impact factor: 13.491

4.  NGEP, a prostate-specific plasma membrane protein that promotes the association of LNCaP cells.

Authors:  Sudipto Das; Yoonsoo Hahn; Satoshi Nagata; Mark C Willingham; Tapan K Bera; Byungkook Lee; Ira Pastan
Journal:  Cancer Res       Date:  2007-02-15       Impact factor: 12.701

5.  RNA interference (RNAi) screening approach identifies agents that enhance paclitaxel activity in breast cancer cells.

Authors:  Joshua A Bauer; Fei Ye; Clayton B Marshall; Brian D Lehmann; Christopher S Pendleton; Yu Shyr; Carlos L Arteaga; Jennifer A Pietenpol
Journal:  Breast Cancer Res       Date:  2010-06-24       Impact factor: 6.466

6.  New gene expressed in prostate: a potential target for T cell-mediated prostate cancer immunotherapy.

Authors:  Vittore Cereda; Diane J Poole; Claudia Palena; Sudipto Das; Tapan K Bera; Cinzia Remondo; James L Gulley; Philip M Arlen; Junko Yokokawa; Ira Pastan; Jeffrey Schlom; Kwong Y Tsang
Journal:  Cancer Immunol Immunother       Date:  2009-06-04       Impact factor: 6.968

Review 7.  Epidemiology of prostate cancer.

Authors:  E David Crawford
Journal:  Urology       Date:  2003-12-22       Impact factor: 2.649

8.  NGEP, a gene encoding a membrane protein detected only in prostate cancer and normal prostate.

Authors:  Tapan K Bera; Sudipto Das; Hiroshi Maeda; Richard Beers; Curt D Wolfgang; Vasantha Kumar; Yoonsoo Hahn; Byungkook Lee; Ira Pastan
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-23       Impact factor: 11.205

9.  Small nucleolar RNA 42 acts as an oncogene in lung tumorigenesis.

Authors:  Y-P Mei; J-P Liao; J Shen; L Yu; B-L Liu; L Liu; R-Y Li; L Ji; S G Dorsey; Z-R Jiang; R L Katz; J-Y Wang; F Jiang
Journal:  Oncogene       Date:  2011-10-10       Impact factor: 9.867

10.  A flexible and accurate genotype imputation method for the next generation of genome-wide association studies.

Authors:  Bryan N Howie; Peter Donnelly; Jonathan Marchini
Journal:  PLoS Genet       Date:  2009-06-19       Impact factor: 5.917

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  20 in total

1.  A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Genes for Pancreatic Cancer Risk.

Authors:  Duo Liu; Dan Zhou; Yanfa Sun; Jingjing Zhu; Dalia Ghoneim; Chong Wu; Qizhi Yao; Eric R Gamazon; Nancy J Cox; Lang Wu
Journal:  Cancer Res       Date:  2020-09-09       Impact factor: 12.701

2.  Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk.

Authors:  Lang Wu; Xiang Shu; Jiandong Bao; Xingyi Guo; Zsofia Kote-Jarai; Christopher A Haiman; Rosalind A Eeles; Wei Zheng
Journal:  Cancer Res       Date:  2019-07-23       Impact factor: 12.701

3.  TBX1 functions as a putative oncogene of breast cancer through promoting cell cycle progression.

Authors:  Shuya Huang; Xiang Shu; Jie Ping; Jie Wu; Jifeng Wang; Chris Shidal; Xingyi Guo; Joshua A Bauer; Jirong Long; Xiao-Ou Shu; Wei Zheng; Qiuyin Cai
Journal:  Carcinogenesis       Date:  2022-02-11       Impact factor: 4.944

4.  Associations Between Genetically Predicted Plasma N-Glycans and Prostate Cancer Risk: Analysis of Over 140,000 European Descendants.

Authors:  Duo Liu; Jingjing Zhu; Tianying Zhao; Sodbo Sharapov; Evgeny Tiys; Lang Wu
Journal:  Pharmgenomics Pers Med       Date:  2021-09-22

5.  Integrating Genome and Methylome Data to Identify Candidate DNA Methylation Biomarkers for Pancreatic Cancer Risk.

Authors:  Jingjing Zhu; Yaohua Yang; John B Kisiel; Douglas W Mahoney; Dominique S Michaud; Xingyi Guo; William R Taylor; Xiao-Ou Shu; Xiang Shu; Duo Liu; Bingshan Li; Ran Tao; Qiuyin Cai; Wei Zheng; Jirong Long; Lang Wu
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2021-09-08       Impact factor: 4.254

6.  Association between lincRNA expression and overall survival for patients with triple-negative breast cancer.

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Journal:  Breast Cancer Res Treat       Date:  2020-11-27       Impact factor: 4.872

7.  A Hierarchical Approach Using Marginal Summary Statistics for Multiple Intermediates in a Mendelian Randomization or Transcriptome Analysis.

Authors:  Lai Jiang; Shujing Xu; Nicholas Mancuso; Paul J Newcombe; David V Conti
Journal:  Am J Epidemiol       Date:  2021-06-01       Impact factor: 4.897

8.  A transcriptome-wide association study identifies novel candidate susceptibility genes for prostate cancer risk.

Authors:  Duo Liu; Jingjing Zhu; Dan Zhou; Emily G Nikas; Nikos T Mitanis; Yanfa Sun; Chong Wu; Nicholas Mancuso; Nancy J Cox; Liang Wang; Stephen J Freedland; Christopher A Haiman; Eric R Gamazon; Jason B Nikas; Lang Wu
Journal:  Int J Cancer       Date:  2021-09-25       Impact factor: 7.396

9.  A transcriptome-wide association study identifies novel blood-based gene biomarker candidates for Alzheimer's disease risk.

Authors:  Yanfa Sun; Dan Zhou; Md Rezanur Rahman; Jingjing Zhu; Dalia Ghoneim; Nancy J Cox; Thomas G Beach; Chong Wu; Eric R Gamazon; Lang Wu
Journal:  Hum Mol Genet       Date:  2021-12-27       Impact factor: 5.121

10.  An integrative multiomics analysis identifies putative causal genes for COVID-19 severity.

Authors:  Lang Wu; Jingjing Zhu; Duo Liu; Yanfa Sun; Chong Wu
Journal:  Genet Med       Date:  2021-06-28       Impact factor: 8.822

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